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Vol. 43. Num. 1.
Pages 1-60 (January - February 2019)
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Vol. 43. Num. 1.
Pages 1-60 (January - February 2019)
DOI: 10.1016/j.medine.2018.10.004
Severity scores in trauma patients admitted to ICU. Physiological and anatomic models
Gravedad en pacientes traumáticos ingresados en UCI. Modelos fisiológicos y anatómicos
L. Serviáa, M. Badiaa, N. Montserrata, J. Trujillanob,
Corresponding author

Corresponding author.
a Servicio de Medicina Intensiva, Hospital Universitario Arnau de Vilanova, Lleida, Spain
b Universidad de Lleida, IRBLLEIDA, Lleida, Spain
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Figures (4)
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Tables (4)
Table 1. Mortality-based demographic characteristics (n=780).
Table 2. Mortality-based scores obtained in risk adjustment models (n=780).
Table 3. Correlation among the different values obtained from mortality risk scoring systems (n=780).
Table 4. Differential characteristics of the group of patients who scored 11–17 in the APACHE II scoring system based on an ISS score above or below 22 points (n=245).
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The goals of this project were to compare both the anatomic and physiologic severity scores in trauma patients admitted to intensive care unit (ICU), and to elaborate mixed statistical models to improve the precision of the scores.


A prospective study of cohorts. The combined medical/surgical ICU in a secondary university hospital. Seven hundred and eighty trauma patients admitted to ICU older than 16 years of age. Anatomic models (ISS and NISS) were compared and combined with physiological models (T-RTS, APACHE II [APII], and MPM II). The probability of death was calculated following the TRISS method. The discrimination was assessed using ROC curves (ABC [CI 95%]), and the calibration using the Hosmer–Lemeshow's H test. The mixed models were elaborated with the tree classification method type Chi Square Automatic Interaction Detection.


A 14% global mortality was recorded. The physiological models presented the best discrimination values (APII of 0.87 [0.84–0.90]). All models were affected by bad calibration (p<0.01). The best mixed model resulted from the combination of APII and ISS (0.88 [0.83–0.90]). This model was able to differentiate between a 7.5% mortality for elderly patients with pathological antecedents and a 25% mortality in patients presenting traumatic brain injury, from a pool of patients with APII values ranging from 10 to 17 and an ISS threshold of 22.


The physiological models perform better than the anatomical models in traumatic patients admitted to the ICU. Patients with low scores in the physiological models require an anatomic analysis of the injuries to determine their severity.

Mortality prediction

Comparar los scores de gravedad anatómicos y fisiológicos en los pacientes traumáticos ingresados en unidad de cuidados intensivos (UCI) y crear modelos combinados que mejoren su precisión.


Estudio prospectivo de cohorte observacional. UCI polivalente de un hospital universitario de 2.° nivel. Se incluyeron los pacientes traumáticos mayores de 16 años ingresados en UCI (n=780). Se comparan los modelos anatómicos (ISS, NISS) con los modelos fisiológicos (T-RTS, APACHE II [APII]), MPM II). La probabilidad de muerte se calculó según metodología TRISS. La discriminación se valoró mediante curvas ROC (ABC [IC 95%]) y la calibración con el estadístico H de Hosmer–Lemeshow. Los modelos combinados se realizaron con metodología de árboles de clasificación tipo Chi Square Automatic Interaction Detection.


Mortalidad global del 14%. Los modelos fisiológicos son los que presentan mejores valores de discriminación (APII con 0,87 [0,84–0,90]). Todos los modelos tienen una mala calibración (p<0,01). El mejor modelo combinado es el que utiliza APII junto a ISS (0,88 [0,83–0,90]) y encuentra un grupo de pacientes (valores de APII entre 10–17) que necesita la puntuación ISS (punto de corte de 22) para diferenciar entre mortalidad del 7,5% asociada a pacientes mayores con antecedentes patológicos y del 25,0% en pacientes con mayor presencia de TCE.


Los modelos fisiológicos presentan ventajas sobre los anatómicos en los pacientes traumáticos ingresados en UCI. Los pacientes con puntuaciones bajas en los modelos fisiológicos requieren del análisis anatómico de las lesiones para determinar su gravedad.

Palabras clave:
Modelos de gravedad
Predicción de mortalidad


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